جستجوی مقالات مرتبط با کلیدواژه « جزیره حرارتی » در نشریات گروه « علوم انسانی »

The purpose of this research is to investigate the relationship between these pollutions in urban areas and heat islands in Ardabil City. In this regard, the land use map of Ardabil City was drawn in the Google Earth Engine system by calling the data of Sentinel 2 and 1 satellites, and its overall accuracy and correctness were checked with the Kappa coefficient. In the next step, to investigate the aerosols of Ardabil City, Sentinel 5 satellite data was used and its daily trend was obtained by regression method. The skewness of aerosols was calculated for 2018-2023 and the pollution density map of Ardabil City was drawn. Then, by calling the MODIS satellite data, the temperature anomaly map and the thermal island of Ardabil City were drawn during 2018-2023, and the night LST trend in the mentioned period and the profile diagram of the night LST thermal island were obtained. By extracting the data of urban aerosol density maps with the thermal islands in ArcGis software, the correlation between temperature and the thermal island of Ardabil City was investigated. The results showed that there is a direct relationship between these two phenomena, such that the amount of daily aerosols in Ardabil City has taken an upward slope since the middle of 2021, and its negative skewness has shown an increase in pollution with high density and occurrence in inner city areas. The pollution density map also showed that the amount of aerosol has increased significantly in the inner city areas and intercity roads of Ardabil City. As a result, the temperature anomaly in urban and residential areas has increased significantly and led to the formation of a thermal island with an average temperature of 8.22 degrees Celsius, which reached its maximum in July.

The role of climate in the study of urban environments is important in terms of its impact on climate change in urban environments. The heat island is one of the hazards that has recently affected the environmental conditions of cities due to urban development.

For this purpose, Landsat ETM satellite images were used during the period 1990-2019. In this regard, LST and NDVI indices, urban coverage and land use were used. Geographical area of research The city of Isfahan has been considered in this study. 

Results and discussion: 

The results showed that the high temperature is mostly in the central core of Isfahan and the surrounding city is covered by the middle temperature class. Most of the low temperature class also includes agricultural use due to high humidity. Parks and green spaces in the city are among the middle temperature classes due to the impact of high and very high temperature areas around them.

In general, it can be said that in the last three periods, the highest area has been related to the average temperature, and this trend will continue in the coming years. Due to the reduction of agricultural land use and the physical expansion of the city, the area of heat islands in the upper range has increased. On the one hand, the reasons for the increase in high temperatures are the increase in population, the increase in industries and the number of cars in the city, the multiplication of traffic volumes, the increase in asphalt levels and urban and interurban roads, and the increase in wasteland due to grazing. He pointed to overcrowding and damage to pastures, as well as clearing of green lands and deforestation.

The surface temperature of the earth is one of the key parameters in the studies of cities.Air pollution is also one of the causes of the creation of heat island in the city, which has been increasing in recent years due to high population density and pollution.The aim was to investigate the temporal changes of urban heat islands and its relationship with air pollution in Kerman in a period of 16 years(2007-2022)And to investigate the trend of temperature changes, the temperature data of Kerman station and the Mann-Kendall test were used, and the data of Kerman air pollution station were used to investigate air pollution.Although the number of polluted days was high, but due to the limited passage of the Badoureh satellite for 16 days from Kerman, the limited number of days with high pollution intensity in Kerman, and the non-compliance of polluted days with the time of satellite passage, finally, seasonal images of five years were selected. The results showed that the temperature of the earth's surface had an upward trend in both seasons, but the heat island occurred only in the summer season.So that in the summer of 2009, the density of very hot temperature was less than 30%, but with the passage of time and in 2022, in the summer season, more than 60% of the urban area has very hot temperature.And parts from the west to the south of the city have formed the center of thermal islands due to the presence of barren lands and also due to the lack of benefit from evaporation and transpiration cooling mechanisms.Also, the correlation between the temperature of the earth's surface and the air pollutants was confirmed at a significant level of 0.01 and 0.05, that in the summer the correlation coefficients are stronger and pollution has also increased.

Land surface temperature (LST) is one of the important parameters in the study of climate change and physical processes of the earth's surface. Rising land temperature causes the phenomenon of heat islands, which is caused by changes in land-use and land cover in urban areas and today has become a major environmental concern. Ahvaz metropolis, as the capital of Khuzestan province in southwestern Iran, has undergone many changes in land-use and land cover in recent years and has enjoyed significant population growth. In recent years, the pattern of unbalanced urban development in Ahvaz has led to the destruction of agricultural lands, vegetation and gardens around the city as one of the most important factors balancing the land surface temperature. This has led to an increase in land surface temperature and the formation of heat islands. The purpose of this study is to investigate land-use changes in Ahvaz and its effects on spatio-temporal patterns of land surface temperature and heat islands in the years 2002-2021.

First, the land-use changes were studied and then, in order to evaluate the relationship between the changes in each Land-use and the land surface temperature, the maximum temperature in each land-use was determined and then the amount of changes was investigated. Landsat 7 ETM+ (2002) and Landsat 8 OLI/TIRS (2013/2020) images downloaded from the USGS. Object-oriented method was used for classification. Educational samples were implemented on the image surface and their corresponding objects were selected as educational samples for each class. The classification was done by SVM algorithm and the user maps were classified into four classes including vegetation, barren areas, constructed areas and water areas. In this study, estimating the LST was performed base on separate window Algorithm and with Landsat 7 ETM+ band 6 and Landsat 8 OLI/TIRS band 11 data. In this Study, LST was estimated using Split-Window (SW) algorithm on Landsat-7 ETM+ and Landsat-8 OLI/TIRS Thermal Infrared (TIR) bands. Then the NDVI values, Vegetation Proportion and Radiated Power were obtained. Finally, The LST value was extracted based on degrees Celsius. In this study, Pearson correlation coefficient was used to investigate the relationship between LST and air temperature. RMSE values was used to compare the estimated temperature by SW algorithm and the measured temperature by Field research. Also, two indices UHII and UHIII were used to calculate the intensity of heat islands. These indices evaluate the LST using the values of vegetation in one area.

According to the results of this study, Kappa coefficients and overall accuracy were 74% and 76% for year 2002 map, 78% and 85% for year 2013 map and 88% and 93% for year 2020 map, respectively. The area of built-up and barren areas has increased and the area of vegetation and water areas has decreased. The rate of increase in land-use of the constructed areas from 2002 to 2020 was about 579.69 hectares and the decrease in vegetation cover was 3200.15 hectares. The barren areas have increased by 2521.66 hectares from 2002 to 2020. Pearson correlation coefficient between air temperature and LST values of 0.65% is obtained, which shows a positive correlation. The RMSe values in comparison with LST and measured temperature by Field research for the images of 2002, 2013 and 2020 was 1.79, 1.66 and 0.98 degrees, respectively. According to the results, the LST values in year 2002 fluctuated about 24.48-42.55, in year 2013 about 26.32-44.47 and in year 2020 about 28.13-46.65 degrees Celsius. The results of LST show an increasing trend of temperature during the period 2020-2020. After estimating the LST, the maximum temperature of each user was determined, which showed the increasing trend of temperature in all applications. The decreasing trend of vegetation has a direct effect on increasing LST in this land-use. The temperature of this land-use has increased by 6.32 degrees in 2002-2020. Over a period of 18 years, the LST in built-up areas and barren areas has increased by 4.10 and 5.26 degrees, respectively. In order to study the spatio-temporal patterns of LST and heat islands, first with NDVI index, vegetation status in each year was divided into three classes of low, medium and high vegetation and then LST values in each category were determined. According to the results, the highest temperature occurred in the floor with low vegetation. The correlation between the two variables LST and NDVI was significant and regression between them showed an inverse correlation that indicated a negative relationship between LST and vegetation. Therefore, vegetation plays an important role in reducing the intensity of the heat island. UHIII index values in the low vegetation class from 0.63 to 0.67, in the medium vegetation class from 0.57 to 0.61 and in the high vegetation class from 0.51 to 0.54 it is arrived. The highest intensity of heat islands in 2002, 2013 and 2020 were in the southern, eastern and northwestern parts of the city, respectively.

According to the research results, land-use changes in the study period have caused an increase in land surface temperature. The highest temperatures have occurred in built-up areas and barren areas; this is due to the increase in the area of built-up and barren areas. Decreased vegetation has a direct effect on increasing LST in this land-use. The NDVI, UHII, UHIII indices and LST values were used to study the spatio-temporal patterns of land surface temperature and heat islands. The results indicate high temperatures in the vegetation with low vegetation. Due to the correlation of NDVI values with land surface temperature and the intensity of heat islands, the necessity and importance of vegetation protection as a very important variable to regulate the air temperature in the city is essential.

Heat waves are one of the climate hazards. The purpose of this research is to investigate the heat waves of Ardabil city and its effect on urban heating from 2003 to 2018. For this purpose by using Fumiaki index, the days where the temperature was +2 standard deviations or higher than the NTD average and lasted for at least 2 days and was defined as a day with heat wave. In order to investigate the effect of heat waves on heat island in the hot and cold months, the heat island for days with a heat wave and a normal day without heat wave with the lowest and maximum temperature before the occurrence of each heat wave during the day and at night of Modis - Aqua was calculated. According to the results, during the studied period, the highest annual and monthly frequency of heat wave in Ardabil was in 2010 and 2016 and in March, April and July. The results also showed that the maximum duration of heat waves was 4 days and therefore short-term. According to the findings, both in the hot months and in the cold months, in both heat wave and no heat wave condition, a cold island is often formed during the day and a heat island is formed at night in Ardabil center. Heat waves, especially in the hot months of the year, have been more than no heat wave conditions. In the summer nights, in the heat wave conditions, the temperature increase up to 4 ºc has also been experienced in the heat island. In total, the results showed that the influence of the heat island on the occurrence of heat waves was higher in hot months than in cold months.

Replacing natural vegetation cover with impermeable urban surfaces) stone, cement, metal, etc.) has resulted in increased land surface temperature which is considered to be the most important problem of urban areas. Distinct temperature difference between the city and the surrounding areas is called heat island (Melkpour et al., 2018). Increased land surface temperature and resulting heat islands in urban areas built without proper preplanning (Khakpour et al., 2016) especially in developing countries such as Iran experiencing a rapid growth rate have resulted in widespread environmental problems. Heat islands mainly occur due to the presence of man-made surfaces which prevent the reflection of sunlight and result in temperature increase. In general, urban heat islands result in increased air and land surface temperature and thermal inversion (Gartland, 2012).

The present study applies a statistical-analytical research method based upon statistical data received from meteorological stations and extracted from satellite images. Climatic data recorded from 1976 to 2020 in Yazd Meteorological Station were retrieved from the General Meteorological Department of Yazd Province and used to measure temperature changes. Urban climate studies mainly take advantage of long-term patterns and thus, the present study has applied the common Man-Kendall method to measure the trend of temperature changes in warm season (July, August, and September). Also, satellite images collected by Landsat 4-8 in a 33-year period, including four statistical periods with a time interval of 11 years (the average recorded in July, August and September of 1987, 1998, 2009 and 2020), have been used to extract heat islands of Yazd city in warm seasons. These images collected under clear weather conditions were retrieved from the United States Geological Survey website (http://glovis.usgs.gov/) in the WGS-1984 UTM image system. NDVI index was used to investigate the vegetation cover. Main land uses discussed in the present study included barren lands, urban areas, vegetation cover and roads. Sample land uses were collected from Google Earth and visually interpreted in ArcMap. Maximum likelihood algorithm was used for the classification process. Finally, Land Surface Temperature was extracted from satellite images and compared with air temperature trend using the Mann-Kendall test.

Results indicate that due to thicker vegetation cover in summer, there has been a negative relationship between the vegetation cover and land surface temperature. In other words, land surface temperature has increased with decreased vegetation cover and vice versa. Types of land use identified in satellite images collected from Yazd city have showed that the city has experienced a widespread physical expansion during the 33-year statistical period regardless of the season under investigation and thus, built-up urban land use class has expanded significantly. As a result, vegetation cover has experienced a negative trend and decreased. Land surface temperature extracted from thermal images of Yazd city has proved parts of northwest and south of the city to be the core of its heat islands. This is due to the presence of barren lands, lack of evapotranspiration mechanisms, high heat absorption capacity and low conduction capacity. Man-Kendall test has found a significant increasing trend for temperature especially in recent years in which the temperature has increased about 2.3 °C. This is most possibly due to the increasing trend of urban population in recent decades, followed by increased residential structures and resulting heat island phenomenon.

In general, classification of urban land use types in Yazd has shown a significant physical expansion of the city during the statistical period. This physical development has occurred in all directions; beginning from the central and northeast-southeast parts, and moving towards northwest-southwest parts. Maximum NDVI was observed in a strip along the central part of Yazd in which vegetation cover is thicker. Green spaces are also observed in some areas of the city. Color spectrum of the LST map has shown relative changes of the ambient temperature in various parts of the city. High and very high temperature (between 41.5 and 50 °C) show the location of the heat islands on LST maps. Also, areas with a deep red color and a temperature above 50 °C have formed hot clusters formed or strengthened between 2009 and 2020 in the west and southwest parts of the city. Satellite images and related graphs have showed that in 2020, Yazd have witnessed a sharp increase in temperature and a heat island.  Temperature data of Yazd Meteorological Station and Man-Kendall test have shown a significant increasing trend (about 2.3°C), especially in recent years. These are related to the urban population growth in recent decades, followed by increased urban structures (residential-commercial) and heat island phenomenon.

Urban expansion leads to the creation of urban heat islands, which can create risks for human health and the environment. Knowledge of the state of vegetation, changes in land use and temperature of each region over time is very important and is used in micro and macro planning. Therefore, the purpose of this research is to investigate the relationship between temperature and vegetation in creating a thermal island in Isfahan city. In this regard, the use of Landsat ETM satellite images during the period of 1990-2019, LST and NDVI indices, and land use were studied and investigated. The results of the investigations show an increase in the size of the city and a decrease in the size of garden lands and marginal pastures of the city. Areas without vegetation are located in the urban area and residential areas and in the southern and eastern heights of Isfahan city. The maximum NDVI index is also in the western and southeastern areas of Isfahan city. The intensity of heat islands is more than other land uses according to the minimum and maximum level and average temperature in urban land and with the increase in the area of ​​residential uses and urban development, the intensity of heat islands has increased. On the other hand, the lowest temperature intensity of heat islands is observed in irrigated agricultural lands and gardens. In general, it can be said that in the city of Isfahan, the high temperature is mostly in the central core of the city, and the surroundings of the city are covered by the middle temperature layer. Low temperatures have also been observed in agricultural use. Parks and urban green spaces also have medium temperature classes due to their proximity to urban uses and being influenced by them. During the studied period, the largest area was related to average temperature and this trend will continue in the coming years.

In recent years, with the increase in the population of cities, urban construction has also increased and as a result, a variety of industrial activities have been developed in them. This has led to the formation of phenomena known as climate wisdom in cities, which has become a major issue in science today. Since the shapeof the organization of spaces in urban blocks plays a significant role in shaping this, so the present study examines the impact of the shape and shape of residential buildings as the most important constituent components of urban blocks. The issue concerns the formation of thermal islands. this study aims to achieve thermal comfort and reduce the effects of heat island phenomena in the space created by mid-rise residential complexes in order to Provide the optimum form of residential complexes for Shiraz. In this regard, the research method used in this article is applied research in terms of purpose and in terms of methodology, quantitative research method is used. Therefore, the research is based on two logical reasoning strategiesin one hand for analyzing library resources is used and on the other hand quantitative measurement is done by using basic form of Envi-met 4 Software. This study has analyzed and compared six different organization in the Shiraz. Hence the temperature data of 12 noon 1 July 1397 has been used as the basis for the summer revolution. The results show that the best condition at the average radiant temperature belongs to the single element central plan.

Alteration of urban forms and geometries due to rapid unplanned urban development can result in localized elevation of land surface temperature - a phenomenon known as urban heat island. This study examins the impact of land development patterns on land surface temperatures in a heterogeneous urban environment. As many as 18 Landsat satellite images for 1995, 2008 and 2021 (average cloudless images per year) were used in this sutdy. First, land development patterns were generated from the processing of Landsat satellite images in SAGA GIS using the method of Stewart and Oke. At the second stage, land surface temperatures for 1995, 2008, and 2021 were extracted using the single-channel algorithm. At the third stage, the relationship between mean value of land surface temperatures and the heterogeneous form of Tehran was analyzed. The results showed that among all LCZs, the highest mean value of land surface temperatures belonged to the Heavy Industry LCZ with the average temperatures of 5.32, 48.18, and 51.87°C for 1995, 2008, and 2021, followed by the Bare Soil/Sand LCZ with the average temperatures of 47.25, 49.25 and 52.36°C for the same years. The lowest mean value of land surface temperatures belonged to the Water LCZ with the average temperatures of 20.5, 22.63, and 23.15°C for 1995, 2008, and 2021, respectively. It was also found that the Compact Low-Rise LCZ had higher mean value of land surface temperatures than both Compact High-Rise and Compact Mid-Rise LCZs. The differences observed between the highest and lowest land surface temperatures in the study area are indicative of the significant impacts of urban form on land surface temperatures. The findings can contribute to our understanding of urban environments and help to devise better plans for minimizing the adverse effects of land use and development on these environments.

The phenomenon of Thermal Island as one of the urban hazards is the result of the way of activity and physical development of cities as well as extensive changes in the land use pattern around cities. The surface temperature of the earth is not only affected by the amount of energy received by the sun, but also by the environmental conditions of the place, especially the reduction of suburban arable land, vegetation degradation and increasing impermeability levels and potentially prone to heat production and pollution. Heated island is a term used to describe the warmer atmosphere and higher temperatures of cities compared to non-urban areas. Determining the geographical distribution and nature of UHI, as well as the factors influencing its occurrence or severity, is something that is now efficient, fast, and inexpensive using satellite imagery and remote sensing techniques. Ahvaz is one of the metropolises with ethnic diversity and mixed subcultures that has experienced a large and rapid increase in population and area over the last three decades and the city has expanded in different directions from south to southwest and north to northeast Has found. One of the prominent consequences of this issue is the emergence and strengthening of the Heated island in this city.

To determine the spatial-place changes of the heated islands of Ahvaz and also to determine its relationship with land use changes, first the Landsat satellite TM sensor images in the last 30 days and Envi software were used and the following main steps were performed:Stage 1 - Preparation of thermal map of the city: To calculate the temperature of the single channel algorithm (SCA) in order to extract LST, an extended infrared thermal band was used and to calculate it, Equation 1 was used. Ts = γ {𝜀1- (YLsensor + Ψ2) + Ψ3} + δ Here are five essential steps you can take to begin the process of preparation for mediation. To calculate each of the parameters in the equation below 5 consecutive steps as described in the headings The first step is to calculate the spectral radius The second step is to calculate the light temperature of the sensor The third step is to calculate the radiative power Step 4, calculate the values of γ and δ Step 5, calculate atmospheric parameters Stage 2: Prepare a land use map using the decision tree: The function of the model is a branch that consists of three levels of decision making and finally to determine the six layers of land cover (including agricultural land, rangeland, irrigated land, heights (Topography), land with little vegetation and built-up lands. In the model run, after applying the preprocessors to the Landsat images, the corresponding images were created for classification using NDVI, DEM, NDWI and LST indices. Setting a threshold for the NDNI index (NDVI> 0.26) vegetation is isolated from other data. In the correct branch, the next node was isolated using NDWI index (NDWI≤0.0) and determination of rangeland class threshold, agricultural land and water. In the third decision-making branch, based on the thresholds defined in the image indices (DEM≥40), DEM topography was determined, Were introduced.

Statistical study of the trend of change in land surface temperature and construction index and the ratio of change of other carabis to urban land uses showed that the trend of change is the average construction of the ascending course and the average temperature of the ascending course and the trend of changes with the transformation process With the expansion of the city of Ahvaz, their vegetation and land have been destroyed and turned into urban lands, and now the thermal island has been directed from the inside of the city to the outskirts. The temperature increase ratio of the urban area was higher than the whole study area.

Based on the results, the temperature of Ahvaz city increased from 282.96 degrees to 287.02 degrees Kelvin between 1988, which shows a growth of 2% and an increase of 4 degrees. Spatially, the highest temperature increase in the city is related to the east and southeast of the city, where agricultural lands and lands with little vegetation have been converted to industrial town and industrial uses and become a source of heat production in this metropolis. Has been. Also in the western part of the city, due to the further expansion of the city and the implementation of residential preparation projects - the NDBI index confirms the same - there has been an increase in temperature. Other influential factors in the spatial change of temperature in these parts of Ahvaz city are the existence of main roads such as Ahvaz-Abadan highway (southern part of the city), Ahvaz-Bandar Imam Khomeini highway (eastern part). Due to the asphalt cover of these routes and more vehicle traffic, they have caused an increase in the thermal map of the region. The lowest temperature in 2020 is related to the areas around the Karun River. Among the factors that have caused the low temperature in this place compared to other parts of Ahvaz in 2020, we can see the existence of the government park, Shahid Chamran University with a lot of green space and low-density residential texture and more open and green space than they  mentioned other parts of the city as well as the wetlands of the last two years. Analysis of the trend of UHI changes and increase in construction using Landsat time series images showed an increase in urban temperature compared to the surrounding area in 1988. This shift in 2020 was due to an increase in regional temperature compared to the city due to river flooding. , Increase in construction and industrial activities in and around the city. Due to the environmental dangers of the Heated island, which directly and indirectly affect urban air pollution, greenhouse gas emissions and global warming, disrupt thermal comfort, increase water and electricity consumption, and exacerbate diseases such as asthma They leave, It is necessary to prevent the change of agricultural use to urban areas, and within the city, between dense textures and industrial areas, by creating vegetation in the form of parks and gardens, tried to prevent the rise in surface temperature.

Investigating the micro-climatic conditions of the city based on data from professional meteorological stations reveals more tangible realities from the urban heat island. In this study, urban heat island was analyzed based on hourly and daily temperature data of automated air-polluting stations under the supervision of Isfahan Municipality's Air Monitoring and Control Center. The validity and accuracy of the data of these stations were confirmed by the correlation and graphical test with the data of the Meteorological Organization's ozone meter station at 99% confidence level. Then the thermal island of the city was obtained based on the temperature difference between the urban and suburban surfaces. The results showed that the annual mean of the thermal island was UHIA = -1.27, indicating no thermal island formation at the annual scale. The minimum heat island in summer is UHIS = -1.55 and the maximum in winter is UHIW = 0.96. Thus, only in winter the average temperature in the city is higher than in the suburbs. Investigation of circadian temperature regime at urban and non-urban levels showed that city temperature at night is higher than the peripheral environment due to higher concentration of urban pollutants due to lower night temperature and temperature inversions especially in cold season. However, due to the reflection of more urban surfaces, the surface temperature of the city is lower than the surrounding environment. Thus, the urban island occurs seasonally in the cold season and in terms of day and night changes. Locally, the isotherm of the urban thermal island is denser and more prominent, mainly in the east and northeast of Isfahan, and the center of the thermal island is concentrated in the northeast of Isfahan.

Studying the spatial pattern of thermal islands with satellite imagery is one of the major challenges in the urban development process of developing countries. If this growth is dispersed and unplanned, many problems and problems will arise in the management and urban planning process.  The purpose of this study is to identify the distribution and temperature difference of different regions of Qom city with respect to its suburbs in order to discover thermal islands and to map its temperature. In this study, using remote sensing and Landslide and OLI and TIRS satellite imagery during six consecutive months from January 1979 to June 1398 cold months to hot months, we investigate the LST surface heat distribution in Qom and its lands. Its margin was scattered in relation to the use and NDVI vegetation index factor. During the research, it is suggested that the thermal islands in Qom be prevented by preventing the destruction of agricultural fields and the construction of urban parks in the desert and open urban areas.

Problem statement:

Urbanization and human activities affect the urban climate and clearly affect the air temperature close to the surface. In Tehran and its satellite, factors such as climatic region, season, time of day and wind regimes, topography, urban environments, population density, residentschr('39') activity, vegetation structure and urban physical form play an important role in the formation of urban heat islands. The purpose of this research is to determine the type of spatial distribution of heat islands of Tehran metropolis and satellite cities using land use and land cover. Replacing natural land cover with impervious surfaces due to urban development has negative environmental, social and economic impacts, in addition to beneficial aspects. Most of the albedo belong to the built areas and the bare land and the smallest of the Albedo belong to the aquatic areas and vegetation. In this research, the hypothesis is whether the suburbs may have higher temperatures than urban areas depending on the type of land use? In fact, it is examined the spatial distribution of the heat island of Tehran and its satellites, in which the use of land and land cover are analyzed as a factor contributing to the creation, intensification or reduction of the thermal island.

Extraction and preparation of imagery data through the Landsat 7 Satellite ETM + sensor over the years 2001-2015 and selection of June as the hottest month of the study area. These images were extracted from Route 164 and Row 35 of the USGS. An assessment was carried out through the accuracy of ground surface temperature data by Landsat satellite images and obtained temperatures from the weather stations in the area based on the Taylor diagram. In order to investigate the spatial structure of the cells obtained in each map, each containing surface temperature and heat island extraction, it used the methods of world spatial autocorrelation (high and low clustering, spatial correlation) and local (Cluster and Outlier analysis, hot spot analysis). The high and low clustering statistics show how the concentration of high or low values ​​in the region. In the next step, the results of analysis of Anselin Local Moran and hot spots were compared in map format. Hot spots were analyzed in all studied regions and in all 7 cities. The area of ​​hot spots was investigated over the course of 15 years and the results were presented in table and diagram form.Land use was surveyed for every 7 county. In the last section were studied, the relationship between hot spots in each city and type and land use changes over 15 years.Surface spatial analysis of the surface temperature of the area showed that the cells follow a cluster pattern and their trend towards clustering. Any kind of land cover and land use will create special features in a place that can be increased or decreased with a specific microclimate.

After selecting the years 2001, 2005, 2010, and 2015 as the sample and survey of the temperature of each land use in that year, it was determined that artifact, pasture, bare lands, forest, aquatic areas, agriculture and green spaces were respectively have the highest to the lowest temperature in the area. On the other hand, in the area of heat island in a region are Rabat Karim, Ray, Islamshahr, Tehran, Shahriar, Karaj and Shemiranat, respectively.In spite of the reduction of aquatic areas and even bare lands, because of the large impact of green space or agricultural land was reduced the extent of heat islands during the statistical period, and on the contrary, the reduction of green space and agricultural land in places where even their forest areas have grown, has increased the levels of heat islands. This suggests that the dispersion and extent of green spaces has a more effective role in reducing the heat island compared with the creation of limited forest and planted surfaces in one place. Hence, in Tehran despite the significant growth of artifacts, due to the increasing growth of green space, the heat islands has been reduced compare with the Ray, Robatkarim and Islamshahr cities, which are exactly on its suburbs.

The high spatial and temporal limitations of TIR images for use in urban climatology have been identified as a current scientific challenge. Therefore, the use of Data Fusion Algorithms in Remote Sensing has been considered. In the old methods, two bands of one sensor were used for Data Fusion. In these methods, a panchromatic band was used to increase spatial accuracy, so only spatial resolution was increased. To solve this problem, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was used to integrate the images of two Landsat and Modis gauges to increase the spatial and temporal resolution of the reflection. but, this algorithm is designed for pixels and unmixing areas that are the same in Modis and Landsat pixels. The use of this model was not suitable for urban areas with a different of landuse. Therefore, the Enhanced STARFM model (ESTARFM) was developed. The ESTARFM model was improved in 2014 to predict thermal radiation and LST, taking into account the annual temperature cycle and the unevenness of the earthchr('39')s surface, and the SADFAT model was introduced.
In this study, the performance of SADFAT model in the use of OLI spatial resolution and MODIS temporal resolution in LST forecast in urban areas was examined. The metropolis of Tehran has different surface covers and multiple microclimates. So if the algorithm works successfully, This model can be used in other cities to improve urban heat island studies. The inputs for the algorithm are thermal radiance of Modis and Landsat   images, the red and near infrared band of Landsat for daily production of LST in 2017 in the city of Tehran. The algorithm uses two pairs of Modis and Landsat images at the same time and sets of Modis images at the time of prediction and then calculate the conversion coefficient for relating the thermal radiance change of a mixed pixel at the coarse resolution to that of a fine resolution. In this way, LST is generated in areas with a variety of landuse.
All the estimated pixels were compared to the base image pixels in that range to evaluate the results of the model. The comparison results for the autumn days with the average correlation coefficient of 0.86 and RMSE equal to 0.122, showed that the model has the highest accuracy in this season and in other seasons with the average correlation coefficient of 0.76 and RMSE about 0.4, has provided good accuracy.
Visual interpretation of the results of SADFAT showed that this model is able to accurately predict the LST of the land cover in different surface coatings and even in areas where one or more urban land uses are mixed in one MODIS pixel.
However, the borders are well separated and the features are not combined. Although the boundaries are clearly defined, in some land uses, the predicted LST is somewhat higher than the observational image.
Landsat and Modis satellites pass through an area with a small time difference, so they are suitable for combining with each other. But in predicting reflectance with the SADFAT algorithm, there are systematic and variable errors that we need to be aware of in order to increase the output accuracy. One of the systematic and unavoidable errors is the instability of the Terra and Aqua satellites passing through at any point, ie at each satellite pass, the location of the study area in Swath and the size of the pixel changes. Due to the distance of the study area from the vertical center of measurement on the ground (Nadir), the amount of this error varies on different days and should be checked for each day. The preventable error is the sudden change in one or more images used (16 days of the same pass time interval for Landsat) is high for estimating surface reflectance with spatial and temporal resolution. These changes may be due to human factors such as air pollution or natural factors. Natural factors such as clouds and dust storms are the main sources of error in using the SADFAT model because they are sudden and temporary and cover a wide area. The occurrence of these two factors has a great impact on reflectance. Therefore, a sudden change in these factors, in one or more images, causes a large error in the calculations.
The study also found minor spatial errors in the prediction, so that even on days when the results were better, points were observed where the values ​​in the predicted LST images did not match exactly with the OLI sensor. The reason for this may be due to changes in vegetation. Although there are some systematic and variable errors in the images and the implementation of the algorithm The results of this study showed that the performance of this model is reliable for predicting the daily LST with a spatial resolution of 30 meters in Tehran.
This method is able to support urban planning activities related to climate change in cities, so it is recommended that its performance be examined separately for different land cover in the city and the efficiency of this algorithm be evaluated with other sensors such as Copernicus Sentinels.

UHI (Urban Heat Island) describes the phenomenon of temperature change in urban areas than their surroundings such as bare lands, gardens. Its effects are: increasing energy and water consuming, escalation of air pollution and intrusion on thermal welfare (Hashemi et al., 2019). Different researches about UHI, have assessed the effect of one or several factors, mainly land use, on the escalation of surface and sensible temperature. There are many researches about this issue. In one case in Macedonia, Skopje, heat island was assessed by using of NDVI index. The results indicated NDVI index was effective in weakening heat island and NDBI index had positive correlation with surface temperature which shows manmade areas have effects on heat island intensification (Kaplan et al., 2018). RS (remote sensing) makes it possible to assess all aspects of UHI as a hazard through preparing high quality satellite images. GIS (geographical information system) does too by preparing database, uniform methods, analysis and producing maps. The objective of this paper is temporal-spatial analysis of heat island of this hazard to recognize the UHI places in relation to land uses. This analysis helps urban managers to know more about spatial requirements in city and the importance of proper places (green lands and parks) to moderate urban temperature.2. Study Area Urmia city is the central district of Urmia county in the center of west Azerbaijan province in Iran. The city has been located in the distance of 18km from Urmia Lake. The city is located in 37 ºN latitude and 45 ºE longitude. Its climatehas beenaffected by latitude, winds, Urmia Lake, Mediterranean wet climate, Siberian cold air masses, topography, altitude, and the direction of altitudes (Javan, 2013).

In this study Landsat images for August period of 1989, 1998, 2011 and 2018 were used. Preprocessing, atmospheric and radiometric correction were performed for the images. To prepare heat island maps, land surface temperature (LST) was calculated by the threshold limit of NDVI and Plank principle method for TM images and Split Window algorithm for TIRS image. The algorithms were run in ENVI 5/3. LST formula factors for TM images included Brightness Temperature and Land Surface Emissivity (LSE). To calculate LST for TIRS bands, Split Window algorithm was run by using some important factors including brightness temperature, split window coefficient values, mean LSE, difference in LSE and atmospheric water vapor content. Using of NDVI and land-use images, the relationship of LST, vegetation cover and different land uses was analyzed. For assessment of heat island intensity changes in Urmia, the index of heat island proportion was used for the images. See the following: temperature of place       Average surface temperature

According to land use maps, during 29 years from 1989 to 2018, Urmia city has had significant growth and expansion. Change detection results indicated  that about 82%, equal to 2475 hectare of bare lands and 72%, equal to 1833 hectare of surrounding farmlands and gardens of the city have been changed to urban land use and related constructions. Using Zonal statistics in Arc GIS the temperature of land uses was assessed .According to the results in 1989 the green cover had the lowest temperature, and the bare lands had the highest average temperature. In August 2018, the maximum temperature is related to urban areas. On August 2018 some new UHIs have been made which are related to producing and industrial workshops, buildings and bare lands in the north east, east and south east of city. The assessment of UHIs changes process showed the escalation of UHI index in Urmia.

Urban Heat Islands have destructive effects for metropolises and the residents. Urmia as a metropolis has had rapid industrial and population growth in the recent decade. In this research assessments have been done by Landsat images from 1989 to 2018 with four years with temporal distances. The results indicated that in 2018 the area of cold and very cold temperature classes have been decreased. It is because of destroying of large areas of farmlands and gardens and changing to urban land use during studied years. In 1989 and 1998 very high temperature class included bare lands. Passing years and constructing new buildings, industrial and production workshops, new UHIs have been created in east, north east and south east in 2018. The results indicated that during the studied period, according to UHI index results, UHI has been intensified. The UHI index with the amount of 0/2 in 1989, has been reached to 0/37 in 2018. According to these results, in addition to extending of UHI in Urmia, UHI has been intensified. Another research which has been done on UHI in Urmia in July 2015 (Asadi et al., 2019) had the same results of this paper. It proved the effect of industrial and administrative land uses on high temperatures. This research represented the negative relation between LST and green lands and vegetables. Maleki et al. (2018) using synoptic stations information and statistics to assess the UHIs in Urmia and recognized the UHIs in same places like this article. This shows that satellite images have high accuracy and efficiency in analyzing natural or manmade phenomena.

Introduction and Background: The growth of cities and the increase in the population and the diverse use of urban lands have caused problems for urban communities. One of these is the phenomenon of heat islands, which is the result of an unusual temperature increase of the city relative to the surrounding countryside. This research tries to achieve a general view on the heat island mechanism, air temperature changes and urban temperature changes in parts of Hamadan city by using TIRS (Landsat 8 satellite images) and comparing it with actual ground level data by statistical methods. The temperature difference of different points from satellite images based on the spectral radiance method and the degree of gray value of pixels in the thermal bond was made using the photo of the Planck equation. Based on the relationship between real data on ground surface temperature at the meteorological station and data extracted from satellite images, according to different regression models, the highest determination coefficient was obtained for three linear, quadratic and cubic correlation methods. Among them, the cubic regression method with the least error was meaningful at 95% confidence level. The high explanatory factor (70% and above) indicates that there is an acceptable coordination between satellite image information and weather station information. The maximum difference between the data taken with the actual ground station data is related to the blanket and minimum temperature of 5.5 and the minimum difference of the green area is 0.5°C. The difference in temperature in different parts of the city is more closely related to the minimum temperature. While the temperature difference in areas covered by green space in Hamadan city with real data is higher at maximum temperature. The results showed that the Hamadan heat islands have a direct relationship with the construction and land use. The temperature changes in different parts of the city of Hamedan are indicative of the creation of heat islands in the non-used building and ground areas. The results of this research can be applied in the management and urban planning and land use of Hamedan.

Urban heat island refers to an area where the temperature is higher than of the surrounding environment. It is referred to as an island since the temperature of a point or an area of the earth's surface (the city) is more than of the surrounding environment, which mostly has, a homogenous and uniform temperature. Therefore, this island, which can be separated and distinguished from the surrounding environment of the city, is named the city of heat island. Urban heat island can be due to growing population and its concentration in the urban centers, and consequently the increase in air pollution. Changes in land use can be regarded as one of the underlying causes of the occurrence of urban heat island. For example, using satellite images to study the heat island in the city of Mashhad, by Mousavi Bayeghi et al. (2012) showed that along with the land use change from the garden level to the city one, there has been a rise in the temperature. Frequent pollution in the city of Isfahan in recent years has led to the development of some hypotheses assuming some relationship between urban heat island and pollution. In this regard, the growing population density and the vertical expansion of the city, as well as urban development, have resulted in the development of the idea that the study of urban heat island in relation to air pollution can be very important as it can help cope with and decrease the degree of urban heat island. With this objective in mind, this study is designed to address this important concern.
The growing intensity of the thermal island due to air pollution in addition to the undesirable effects on human health can seriously damage the valuable historical works in the popular tourist city of Isfahan. It is hoped that the results of this research could help reduce the effects of the thermal island, leading to the development a better living environment in the city of Isfahan accordingly. Methods based on Satellite images can be regarded as one of the best ones for studying the thermal island; in fact, such methods have been used in many studies inside and outside the country. In this research, the thermal island in the city of Isfahan has also been analyzed using satellite imagery. In order to study urban heat island in the city of Isfahan, a series of landsat 8 satellite images with good resolution were used. This satellite conducts imaging through 11 spectral bands. The bands 1 to 9, which are known as OLI, carry out imaging in color and NIR spectra. The bands 10 and 11 are well-known as TIRS thermal bands. They do imaging within long infrared waves. In this study, the bands 4, representing red, and 5, representing the near-infrared, and the thermal bands 10 and 11 were used to study the urban island in the city of Isfahan. The data related to AQI air quality index was used to check days with air pollution. Due to the restrictions over the passage of satellite within a period of 16 days over the city of Isfahan, the limited number of days with extremely high pollution in the city, and the non-conformity between polluted days and the time of satellite passage, images of three days representing the very unhealthy (the red condition), unhealthy (the orange condition), and healthy (yellow condition) air were thus used. In this study, Subrino Split-Window algorithm was used as the technique to calculate the Earth's surface temperature. This method is based on the calculation of brightness temperature of the bands 10 and 11 as well as the vegetation index of the bands 4 and 5. For this purpose, Arc_GIS10.3 software was used to compute the Earth's surface temperature and the air temperature of the city. ENVI software was also used for the atmospheric correction. Isfahan, due to climatic conditions and a flat topography, has a relatively quiet atmosphere throughout the year. Although Mount Soffeh is located in the south-west of the city, this mountain can only help reduce the speed of westward winds over the city as it is a single peak with a low height. In addition, the vertical expansion of buildings in all parts of the city causes the wind speed to be slow due to the increased friction. High buildings with greater height than the other points, especially in the western part of Isfahan, have led to the considerable reduction of wind speed, which is an important parameter. On the other hand, population growth and its concentration in the central part of the city have increased the intensity of urban heat island. To address the possible relationship between air pollution and urban heat island, the date of January 22nd, 2014 was chosen for investigation. On this day, the temperature calculated from satellite images of the city was within the range of 3 and 17 degrees Celsius. In general, the temperature fluctuated between 5 and 9 ° C in most parts of the city, and the 7° C isotherm bypassed most parts of the city.
The correlation coefficient between vegetation index (NDVI) and land surface temperature, LST, was equal to the 0/37064, which was significant at the confidence level of 99%. Given that the urban heat island is based on urban atmospheric temperature, not the temperature of emitting or reflecting surfaces, some empirical relationships were used to convert surface temperature to air temperature. Accordingly, it was found that the air temperature in the city fluctuated between +5.5 and -1.8 ° C on January 22nd, 2014.
The comparison of the city thermal island map with the map of pollution distribution confirmed the increase in the city temperature as a result of urban air pollution.
That is, the highest concentration of pollution in the East and North East of related to the areas with the higher air temperature. The observed maximum temperature shown by the color red in the map was 13.8 degrees and this was 10.6 degrees in the suburbs. Temperature difference between the city heat-island and suburban areas on this days reached to 3.2 degrees Celsius.
The highest rates of pollution were observed in the stations located in the Eastern Isfahan, including the Ahmadabad SQ and Kharazi Highway. Correlation analysis between the earth's surface temperature map and the map of the distribution of air quality index in the city of Isfahan showed a correlation coefficient of 0.242 at 99% confidence level on January 22nd, 2014. On this day, air pollution AQI index was between 117 to 169, and the temperature ranged from 8.5 to 13.7 degrees Celsius. The city of Isfahan, due to stable climatic conditions at most times of the year and the spread of pollution, is one of the most polluted cities in Iran. The increased intensity of thermal island is one consequence of this phenomenon. In this study, Landsat 8 satellite images with a high resolution were used to estimate the surface temperature of the Earth. The temperature calculated by the model was compared with the soil temperature at the meteorological stations. A slight difference between the temperature in soil at the depth of 5 centimeters and the LST obtained through satellite images, which ranged from a maximum of 6 to a minimum of 1.8, showed that the Subrino's Split Window method could be suitable for estimating the surface temperature of the earth. Finally, the urban heat island in the city of Isfahan was obtained based on the statistical relationships between the land surface temperature (LST) and the air temperature. The analysis of topographic profile related to thermal island temperature showed the promotion of the thermal island in the city as compared with the surrounding area. That is, the temperature inside the city was 7.3 degrees and 9.5 degrees Celsius warmer than the surrounding area respectively, which could show the city's urban heat island clearly. The difference between the temperature of the city's thermal island and the city's surrounding temperature was higher at the time of the maximum pollution. The comparison of the temperature maps of Isfahan with the pollution distribution maps revealed the maximum correlation between temperature and the pollutant areas. The correlation coefficient between the pollution distribution map and the urban temperature map was positive and significant. In more polluted days, the linear relationship between the pollution increase and urban air temperature increase was stronger. As a result of the increased air pollution, the intensity of the thermal island of the city was aggravated. The study of air pollution distribution in the city of Isfahan showed that the eastern regions had more contamination. This was influenced by the urban topography. This is because the southern and western parts of Isfahan are at a higher elevation due to the presence of Mount Soffeh, and the pollution due to mass weight tends to subside in the lower northern and eastern regions of Isfahan. On the other hand, pollution is more concentrated in the eastern regions of the city due to the slow prevailing western winds. The comparison of the thermal map of the thermal Island in the city of Isfahan to the pollution distribution map confirmed the effect of pollution on the increase of urban air temperature. Therefore, the most pollution was concentrated in the eastern and northeastern Isfahan, which were the areas with the higher air temperature. The observed maximum temperature reached to 13.8 degrees, whereas it was 10.6 degrees in the suburbs of Isfahan.

The simplest definition of urbanization is that urbanization is the process of becoming urban. Urban climate is defined by specific climate conditions which differ from surrounding rural areas. Urban areas, for example, have higher temperatures than surrounding rural areas and weaker winds. Land Surface Temperature is an important phenomenon in global climate change. As the green house gases in the atmosphere increases, the LST will also increase. Energy and water exchanges at the biosphere–atmosphere interface have major influences on the Earth's weather and climate. Numerical models ranging from local to global scales must represent and predict effects of surface fluxes. The urban thermal environment is influenced by the physical characteristics of the land surface and by human socioeconomic activities. The thermal environment can be considered to be the most important indicator for representing the urban environment. Vegetation is another important component of the urban ecosystem that has been the subject of much basic and applied research. Urban vegetation influences the physical environment of cities through selective absorption and reflection of incident radiation and regulation of latent and sensible heat exchange Satellite-borne instruments can provide quantitative physical data at high spatial or temporal resolutions. Visible and near-infrared remote sensing systems have been used extensively to classify phenomena such as city growth, land use /cover changes, vegetation index and population statistics. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted Normalized Difference Vegetation Index and Heat Island Intensity.
I conducted all spatial analysis in the UTM Zone 39 Northern Hemisphere projection. The fundamental procedure I used for evaluating change in land surface temperature was to relative temperature for both images, so that the values are temperature difference between the coldest and hottest areas in Tehran metropolitan. subtracting these images from each other results in relative temperature change from 2003 to 2015. Landsat satellite data were used to extract land use/land cover information and their changes for the abovementioned cities. Land surface temperature was retrieved from Landsat thermal images. The relationship between land surface temperature and landuse /land-cover classes, as well as the normalized vegetation index (NDVI) was analyzed.
In this study, LST for Tehran metropolitan was derived using SW algorithm with the use of Landsat 8 Optical Land Imager (OLI) of 30 m resolution and Thermal Infrared Sensor (TIR) data of 100 m resolution. SW algorithm needs spectral radiance and emissivity of two TIR bands as input for deriving LST. The spectral radiance was estimated using TIR bands 10 and 11. Emissivity was derived with the help of land cover threshold technique for which OLI bands 2, 3, 4 and 5 were used. The output revealed that LST was high in the barren regions whereas it was low in the hilly regions because of vegetative cover. As the SW algorithm uses both the TIR bands (10 and 11) and OLI bands 2, 3, 4 and 5, the LST generated using them were more reliable and accurate. NDVI negatively affected LST and Urban Heat Island in vegetation areas in 2003 and 2015 in Tehran metropolitan. This analysis provides an effective tool in evaluating the environmental influences of zoning in urban ecosystems with remote sensing and geographical information systems. This method exhibits a promising performance in UHI forecast. The predicted LST confirms that urban growth has severely influenced UHI pattern through expanding the hot area. Our study confirmed that LST prediction performance is strongly depended on the resolution.
The results reveal that the urban LST is affected mainly by the land surface characteristics and has a close relation to the abundance of vegetation greenness. The spatial distance from the UHI centre is another important factor influencing the LST in some areas. The methodology presented in this paper can be broadly applied in other metropolitans which exhibit a similar dynamic growth. Our findings can represent a useful tool for policy makers and the community awareness of environmental assessment by providing a scientific basis for sustainable urban planning and management. This provides an effective tool in evaluating the vegetation greenness of different zoning in urban ecosystems with remote sensing and geographical information systems. From the perspective of land use planning and urban management, it is recommend that planners and policy makers should pay serious attention to future land use policies that maintain a relevant proportion of public space, green areas, and land surface physical characteristics.

Urban climate is strongly influenced by the processes of urban work and life. Expansion of cities and consequently increased human constructions causes to changes in urban climate. The rising temperature of cities rather than the surroundings is one of the effects linked to direct human intervention.
Building heating, air pollution and the use of inappropriate materials in the flooring streets (like asphalt streets due to dark colors in energy-absorption) are effective in phenomenon of urban heat islands that makes unfavorable environment for citizens. Paying attention to the urban surfaces like sidewalk, streets and rooftops has a great role in decreasing effect of this phenomenon. Due to growing urbanization and subsequently cities development, urban heat islands have taken a growing trend in big cities.
In general, the urban heat-island is a result of urbanity features, air pollution, human warmth, presence of impervious surfaces in the city, thermal properties of materials and geometry of urban areas. Heat island phenomenon is a result of many factors that are summarized below: (1) urban Geometry (morphometry) (2) thermal properties of materials which increase the sensible heat storage in the urban texture (3) released human heat as a result of fuel combustion and animal metabolism (4) urban greenhouse gases, leading to an increase in long wave radiation, atmospheric contamination and therefore warmer atmosphere (5) reduction of evaporation levels in cities, which means that energy will be released more as tangible rather than latent heat (6) reduction of turbulence and heat transfer through the streets.
This study aimed to simulate and calculate the maximum amount of heat island (UHI max) according to the conditions of urban geometry in the region of Kucheh bagh in Tabriz that is a pioneer study in Iran.
The study area is located in Kuche bagh region at the intersection of the streets of Ghods and Farvardin in the city of Tabriz.
The Oke’s numerical-theoretical equation was used for this study. First, the geometry of the target area using the radius of 15 meters from the axis of the road was divided into separate blocks. The ratio of street width (W) and height of buildings (H) was calculated in GIS software and at the end, the intensity of UHImax was calculated and simulated using Oke equation.
The urban geometry including building height and street width is calculated using Equation 1.
The theoretical- numerical basis of this equation shows that simulation of H/W ratio is an appropriate ways to describe urban geometry. Increasing the value of this ratio could lead to an increase in urban heat-island through modeling. This model has many advantages compared to other methods used to estimate the urban heat island. So, the selected parameter to calculate urban geometry and the model used to estimate the maximum intensity of heat island is the ratio of H / W and OKE model, respectively. In addition, the average height of buildings located within a radius of 15 meters and an average width of passages were calculated from the equation 2 and 3, respectively.
After calculating the geometry of the study area, the results showed that the blocks E, G and D in terms of height of the buildings have a heterogeneous distribution, but the distribution of blocks C, I and J is illustrative of their standard configuration. Although the blocks E, F and J in terms of street width are less diverse compared to other blocks, but in terms of height of buildings (8.6, 7 and 5 meters) have a different pattern that maximum values of their UHI are 8.3, 7.5 and 6.3 degrees, respectively. Three blocks B, H and I, in addition to their similarity according to street width and height of the buildings, in terms of the ratio of H / W and heat island intensity with the values of 9.6, 9.8 and 10.2 degrees are homogeneous.
It was also found that the greatest difference between the H / W ratio is related to block A (0.54) and block H (1.98); this difference has caused that greatest difference between the maximum intensity of UHI would calculated between the two blocks equal to 5.2 degree.
Misconfiguration causes that energy leaving from city surface deal with the problem due to narrow passages and high buildings. Therefore, consideration appropriate width of passages and streets and height of buildings are necessary to ease heat leaving and reduce intensity of UHI.
These simulations showed that high buildings and narrow streets intensify the heat islands. While in the presence of short buildings and wide streets, the UHI max is lowered. When the ratio H / W in the studied urban area is between 0.54 to 0.81, UHI max remains between 5 to 6.6 C˚, when this ratio increases to 1.01 to 1.98, UHI max will be between 7.5 and 10.2 C˚. The result also revealed that block A and H with 5 and 10.2 C˚ have the minimum and maximum value of UHI intensity, respectively. So can be concluded that block A and H have the most standard and non-standard urban configuration in the region. The estimates from regression model showed that the street width (91.6%) is more effective than the height of the buildings (6.6%) in changing UHI max.